Conventional and alternative pest management strategies: a comparative proteomic study on musts

The odors of wines are diverse, complex and dynamic and much research has been devoted to the understanding of their chemical bases. However, while the “basic” chemical part of the problem, namely the identity of the chemicals responsible for the different odor nuances, was satisfactorily solved years ago, there are some relevant questions precluding a clear understanding. These questions are related to the physicochemical interactions determining the effective volatilities of the odorants and, particularly, to the perceptual interactions between different odor molecules affecting in different ways to the final sensory outputs.

The purpose of the present study was to understand the overall concept of an aged dry white wine using a descriptive mental questionnaire. A total of 680 worldwide participants, grouped according to their involvement in the wine business, replied to an online questionnaire to characterize the sensory analytical and synthetic descriptors of an aged dry white wine. The descriptors were selected using a Check-All-That-Apply (CATA) approach concerning wine colour, aroma, taste, mouthfeel, and global appreciation.

Grapes are one of the world’s primary fruit crops, and pruning activities generate high amounts of annual wood wastes [1]. These pruning shoots contain valuable phenolic compounds and could have numerous potential applications [1,2]. Consequently, the aim of this work was to evaluate the physico-chemical properties of vine pruning residues with potential as enological additives. For this purpose, grapevine shoots from 12 varieties grown in Chile were collected during the winter of 2021.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

The context of climate crisis leads to the acceleration of technological ripening of grapes, with unsuitable loss of acidity, so various vineyard management alternatives are being considered to delay the grape ripening. The delay of the vegetative cycle towards a period of milder temperatures affects ripening, but vine behavior can vary according to the area, conduction, watering, variety, etc. A work is proposed to know the response to the green pruning of shoots, executed in fruit set and in pea size, in cv. Verdejo.